Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations1048532
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory918.0 MiB
Average record size in memory918.1 B

Variable types

Categorical5
Text9
DateTime1
Numeric1

Alerts

Application Number has unique values Unique

Reproduction

Analysis started2025-03-25 17:53:42.601623
Analysis finished2025-03-25 17:54:16.988145
Duration34.39 seconds
Software versionydata-profiling vv4.15.1
Download configurationconfig.json

Variables

Gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.9 MiB
Male
576434 
Female
461543 
Other
 
10555

Length

Max length6
Median length4
Mean length4.8904268
Min length4

Characters and Unicode

Total characters5127769
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowMale
4th rowMale
5th rowFemale

Common Values

ValueCountFrequency (%)
Male 576434
55.0%
Female 461543
44.0%
Other 10555
 
1.0%

Length

2025-03-25T23:24:17.068063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T23:24:17.149565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
male 576434
55.0%
female 461543
44.0%
other 10555
 
1.0%

Most occurring characters

ValueCountFrequency (%)
e 1510075
29.4%
a 1037977
20.2%
l 1037977
20.2%
M 576434
 
11.2%
F 461543
 
9.0%
m 461543
 
9.0%
O 10555
 
0.2%
t 10555
 
0.2%
h 10555
 
0.2%
r 10555
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5127769
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1510075
29.4%
a 1037977
20.2%
l 1037977
20.2%
M 576434
 
11.2%
F 461543
 
9.0%
m 461543
 
9.0%
O 10555
 
0.2%
t 10555
 
0.2%
h 10555
 
0.2%
r 10555
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5127769
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1510075
29.4%
a 1037977
20.2%
l 1037977
20.2%
M 576434
 
11.2%
F 461543
 
9.0%
m 461543
 
9.0%
O 10555
 
0.2%
t 10555
 
0.2%
h 10555
 
0.2%
r 10555
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5127769
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1510075
29.4%
a 1037977
20.2%
l 1037977
20.2%
M 576434
 
11.2%
F 461543
 
9.0%
m 461543
 
9.0%
O 10555
 
0.2%
t 10555
 
0.2%
h 10555
 
0.2%
r 10555
 
0.2%

State/UT
Categorical

Distinct36
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.9 MiB
Gujarat
195645 
Maharashtra
109067 
Uttar Pradesh
100076 
Rajasthan
85373 
Karnataka
60518 
Other values (31)
497853 

Length

Max length40
Median length17
Mean length9.8944448
Min length3

Characters and Unicode

Total characters10374642
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKerala
2nd rowTripura
3rd rowGujarat
4th rowRajasthan
5th rowHaryana

Common Values

ValueCountFrequency (%)
Gujarat 195645
18.7%
Maharashtra 109067
 
10.4%
Uttar Pradesh 100076
 
9.5%
Rajasthan 85373
 
8.1%
Karnataka 60518
 
5.8%
Telangana 59295
 
5.7%
Andhra Pradesh 55231
 
5.3%
Madhya Pradesh 40553
 
3.9%
Tamil Nadu 34783
 
3.3%
Haryana 20687
 
2.0%
Other values (26) 287304
27.4%

Length

2025-03-25T23:24:17.243738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pradesh 212190
15.1%
gujarat 195645
13.9%
maharashtra 109067
 
7.8%
uttar 100076
 
7.1%
rajasthan 85373
 
6.1%
karnataka 60518
 
4.3%
telangana 59295
 
4.2%
andhra 55231
 
3.9%
and 41635
 
3.0%
madhya 40553
 
2.9%
Other values (37) 444885
31.7%

Most occurring characters

ValueCountFrequency (%)
a 2616247
25.2%
r 1048409
10.1%
h 823410
 
7.9%
t 724673
 
7.0%
n 506242
 
4.9%
s 501672
 
4.8%
d 498242
 
4.8%
e 362298
 
3.5%
355936
 
3.4%
u 319486
 
3.1%
Other values (33) 2618027
25.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10374642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 2616247
25.2%
r 1048409
10.1%
h 823410
 
7.9%
t 724673
 
7.0%
n 506242
 
4.9%
s 501672
 
4.8%
d 498242
 
4.8%
e 362298
 
3.5%
355936
 
3.4%
u 319486
 
3.1%
Other values (33) 2618027
25.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10374642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 2616247
25.2%
r 1048409
10.1%
h 823410
 
7.9%
t 724673
 
7.0%
n 506242
 
4.9%
s 501672
 
4.8%
d 498242
 
4.8%
e 362298
 
3.5%
355936
 
3.4%
u 319486
 
3.1%
Other values (33) 2618027
25.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10374642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 2616247
25.2%
r 1048409
10.1%
h 823410
 
7.9%
t 724673
 
7.0%
n 506242
 
4.9%
s 501672
 
4.8%
d 498242
 
4.8%
e 362298
 
3.5%
355936
 
3.4%
u 319486
 
3.1%
Other values (33) 2618027
25.2%
Distinct733
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T23:24:17.534337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length22
Mean length8.4228846
Min length3

Characters and Unicode

Total characters8831664
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPalakkad
2nd rowSepahijala
3rd rowDang
4th rowBikaner
5th rowRohtak
ValueCountFrequency (%)
north 19069
 
1.6%
south 18096
 
1.5%
west 11082
 
0.9%
east 10723
 
0.9%
goa 10574
 
0.9%
sikkim 10511
 
0.9%
mumbai 10326
 
0.8%
chandigarh 10064
 
0.8%
kachchh 9899
 
0.8%
kheda 9846
 
0.8%
Other values (736) 1094709
90.1%
2025-03-25T23:24:17.852690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1785372
20.2%
r 728037
 
8.2%
h 558971
 
6.3%
i 527868
 
6.0%
n 513284
 
5.8%
u 426491
 
4.8%
d 337847
 
3.8%
o 324753
 
3.7%
l 308023
 
3.5%
g 267500
 
3.0%
Other values (44) 3053518
34.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8831664
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1785372
20.2%
r 728037
 
8.2%
h 558971
 
6.3%
i 527868
 
6.0%
n 513284
 
5.8%
u 426491
 
4.8%
d 337847
 
3.8%
o 324753
 
3.7%
l 308023
 
3.5%
g 267500
 
3.0%
Other values (44) 3053518
34.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8831664
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1785372
20.2%
r 728037
 
8.2%
h 558971
 
6.3%
i 527868
 
6.0%
n 513284
 
5.8%
u 426491
 
4.8%
d 337847
 
3.8%
o 324753
 
3.7%
l 308023
 
3.5%
g 267500
 
3.0%
Other values (44) 3053518
34.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8831664
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1785372
20.2%
r 728037
 
8.2%
h 558971
 
6.3%
i 527868
 
6.0%
n 513284
 
5.8%
u 426491
 
4.8%
d 337847
 
3.8%
o 324753
 
3.7%
l 308023
 
3.5%
g 267500
 
3.0%
Other values (44) 3053518
34.6%
Distinct56
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.6 MiB
2025-03-25T23:24:18.065144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length69
Median length58
Mean length47.591023
Min length10

Characters and Unicode

Total characters49900711
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKerala State Electricity Board (KSEB)
2nd rowTripura State Electricity Corporation Limited (TSECL)
3rd rowTorrent Power Limited, Ahmedabad
4th rowJodhpur Vidyut Vitran Nigam Limited (JdVVNL)
5th rowDakshin Haryana Bijli Vitran Nigam (DHBVN)
ValueCountFrequency (%)
limited 701746
 
11.0%
company 443405
 
6.9%
power 322743
 
5.0%
corporation 250322
 
3.9%
distribution 221350
 
3.5%
electricity 196564
 
3.1%
of 183805
 
2.9%
vidyut 170981
 
2.7%
vij 151302
 
2.4%
gujarat 151302
 
2.4%
Other values (125) 3598673
56.3%
2025-03-25T23:24:18.420753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5343661
 
10.7%
i 4255684
 
8.5%
a 3956896
 
7.9%
t 3301035
 
6.6%
r 3052156
 
6.1%
o 2637889
 
5.3%
n 2274121
 
4.6%
e 2266211
 
4.5%
d 1819627
 
3.6%
m 1716762
 
3.4%
Other values (41) 19276669
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49900711
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5343661
 
10.7%
i 4255684
 
8.5%
a 3956896
 
7.9%
t 3301035
 
6.6%
r 3052156
 
6.1%
o 2637889
 
5.3%
n 2274121
 
4.6%
e 2266211
 
4.5%
d 1819627
 
3.6%
m 1716762
 
3.4%
Other values (41) 19276669
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49900711
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5343661
 
10.7%
i 4255684
 
8.5%
a 3956896
 
7.9%
t 3301035
 
6.6%
r 3052156
 
6.1%
o 2637889
 
5.3%
n 2274121
 
4.6%
e 2266211
 
4.5%
d 1819627
 
3.6%
m 1716762
 
3.4%
Other values (41) 19276669
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49900711
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5343661
 
10.7%
i 4255684
 
8.5%
a 3956896
 
7.9%
t 3301035
 
6.6%
r 3052156
 
6.1%
o 2637889
 
5.3%
n 2274121
 
4.6%
e 2266211
 
4.5%
d 1819627
 
3.6%
m 1716762
 
3.4%
Other values (41) 19276669
38.6%
Distinct366
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size8.0 MiB
Minimum2024-01-01 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-03-25T23:24:18.517627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-25T23:24:18.627406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
Rejected
736858 
Accepted
311674 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8388256
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccepted
2nd rowRejected
3rd rowAccepted
4th rowRejected
5th rowAccepted

Common Values

ValueCountFrequency (%)
Rejected 736858
70.3%
Accepted 311674
29.7%

Length

2025-03-25T23:24:18.748800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T23:24:18.796617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
rejected 736858
70.3%
accepted 311674
29.7%

Most occurring characters

ValueCountFrequency (%)
e 2833922
33.8%
c 1360206
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736858
 
8.8%
R 736858
 
8.8%
A 311674
 
3.7%
p 311674
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2833922
33.8%
c 1360206
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736858
 
8.8%
R 736858
 
8.8%
A 311674
 
3.7%
p 311674
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2833922
33.8%
c 1360206
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736858
 
8.8%
R 736858
 
8.8%
A 311674
 
3.7%
p 311674
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8388256
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2833922
33.8%
c 1360206
16.2%
d 1048532
 
12.5%
t 1048532
 
12.5%
j 736858
 
8.8%
R 736858
 
8.8%
A 311674
 
3.7%
p 311674
 
3.7%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.0 MiB
3 - 4 KW
733792 
4 - 5 KW
154372 
5 - 6 KW
77713 
2 - 3 KW
 
57978
Above 6 KW
 
20653

Length

Max length10
Median length8
Mean length8.0393941
Min length8

Characters and Unicode

Total characters8429562
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3 - 4 KW
2nd row3 - 4 KW
3rd row4 - 5 KW
4th row2 - 3 KW
5th row3 - 4 KW

Common Values

ValueCountFrequency (%)
3 - 4 KW 733792
70.0%
4 - 5 KW 154372
 
14.7%
5 - 6 KW 77713
 
7.4%
2 - 3 KW 57978
 
5.5%
Above 6 KW 20653
 
2.0%
1 - 2 KW 4024
 
0.4%

Length

2025-03-25T23:24:18.874787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-25T23:24:18.953430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
kw 1048532
25.1%
1027879
24.6%
4 888164
21.3%
3 791770
19.0%
5 232085
 
5.6%
6 98366
 
2.4%
2 62002
 
1.5%
above 20653
 
0.5%
1 4024
 
0.1%

Most occurring characters

ValueCountFrequency (%)
3124943
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027879
 
12.2%
4 888164
 
10.5%
3 791770
 
9.4%
5 232085
 
2.8%
6 98366
 
1.2%
2 62002
 
0.7%
A 20653
 
0.2%
Other values (5) 86636
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8429562
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3124943
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027879
 
12.2%
4 888164
 
10.5%
3 791770
 
9.4%
5 232085
 
2.8%
6 98366
 
1.2%
2 62002
 
0.7%
A 20653
 
0.2%
Other values (5) 86636
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8429562
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3124943
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027879
 
12.2%
4 888164
 
10.5%
3 791770
 
9.4%
5 232085
 
2.8%
6 98366
 
1.2%
2 62002
 
0.7%
A 20653
 
0.2%
Other values (5) 86636
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8429562
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3124943
37.1%
W 1048532
 
12.4%
K 1048532
 
12.4%
- 1027879
 
12.2%
4 888164
 
10.5%
3 791770
 
9.4%
5 232085
 
2.8%
6 98366
 
1.2%
2 62002
 
0.7%
A 20653
 
0.2%
Other values (5) 86636
 
1.0%

Application Number
Real number (ℝ)

Unique 

Distinct1048532
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55047752
Minimum10000049
Maximum99999677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 MiB
2025-03-25T23:24:19.064883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10000049
5-th percentile14540485
Q132527149
median55087246
Q377557472
95-th percentile95530472
Maximum99999677
Range89999628
Interquartile range (IQR)45030324

Descriptive statistics

Standard deviation25974284
Coefficient of variation (CV)0.47185005
Kurtosis-1.1997775
Mean55047752
Median Absolute Deviation (MAD)22513646
Skewness-0.0011243218
Sum5.7719329 × 1013
Variance6.7466345 × 1014
MonotonicityNot monotonic
2025-03-25T23:24:19.175499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68871853 1
 
< 0.1%
93008687 1
 
< 0.1%
49656872 1
 
< 0.1%
40395980 1
 
< 0.1%
53218604 1
 
< 0.1%
33535665 1
 
< 0.1%
78345035 1
 
< 0.1%
47519114 1
 
< 0.1%
97784656 1
 
< 0.1%
62241489 1
 
< 0.1%
Other values (1048522) 1048522
> 99.9%
ValueCountFrequency (%)
10000049 1
< 0.1%
10000052 1
< 0.1%
10000144 1
< 0.1%
10000229 1
< 0.1%
10000247 1
< 0.1%
10000252 1
< 0.1%
10000486 1
< 0.1%
10000489 1
< 0.1%
10000608 1
< 0.1%
10000612 1
< 0.1%
ValueCountFrequency (%)
99999677 1
< 0.1%
99999661 1
< 0.1%
99999642 1
< 0.1%
99999640 1
< 0.1%
99999621 1
< 0.1%
99999488 1
< 0.1%
99999258 1
< 0.1%
99999135 1
< 0.1%
99999114 1
< 0.1%
99998895 1
< 0.1%
Distinct379
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
2025-03-25T23:24:19.359090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5944959
Min length8

Characters and Unicode

Total characters9011604
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-15
2nd rowDeclined
3rd row2024-12-01
4th rowDeclined
5th row2024-09-30
ValueCountFrequency (%)
declined 736858
70.3%
2024-07-21 1572
 
0.1%
2024-07-16 1565
 
0.1%
2024-07-22 1557
 
0.1%
2024-07-30 1550
 
0.1%
2024-07-18 1525
 
0.1%
2024-07-15 1524
 
0.1%
2024-08-01 1521
 
0.1%
2024-07-27 1519
 
0.1%
2024-07-24 1515
 
0.1%
Other values (369) 297826
28.4%
2025-03-25T23:24:19.751204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1473716
16.4%
2 801024
8.9%
D 736858
8.2%
c 736858
8.2%
i 736858
8.2%
l 736858
8.2%
n 736858
8.2%
d 736858
8.2%
0 680207
7.5%
- 623348
6.9%
Other values (8) 1012161
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9011604
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1473716
16.4%
2 801024
8.9%
D 736858
8.2%
c 736858
8.2%
i 736858
8.2%
l 736858
8.2%
n 736858
8.2%
d 736858
8.2%
0 680207
7.5%
- 623348
6.9%
Other values (8) 1012161
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9011604
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1473716
16.4%
2 801024
8.9%
D 736858
8.2%
c 736858
8.2%
i 736858
8.2%
l 736858
8.2%
n 736858
8.2%
d 736858
8.2%
0 680207
7.5%
- 623348
6.9%
Other values (8) 1012161
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9011604
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1473716
16.4%
2 801024
8.9%
D 736858
8.2%
c 736858
8.2%
i 736858
8.2%
l 736858
8.2%
n 736858
8.2%
d 736858
8.2%
0 680207
7.5%
- 623348
6.9%
Other values (8) 1012161
11.2%
Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.1 MiB
SkyPower Solar
 
70095
GreenRay Solar Systems
 
69918
SunWave Energy
 
68786
SunRise Renewable Solutions
 
68526
PowerSun Technologies
 
65982
Other values (15)
705225 

Length

Max length27
Median length23
Mean length19.11131
Min length13

Characters and Unicode

Total characters20038820
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSkyPower Solar
2nd rowGreenEnergy Systems
3rd rowEcoPower Solar
4th rowGreenRay Solar Systems
5th rowBrightSun Power

Common Values

ValueCountFrequency (%)
SkyPower Solar 70095
 
6.7%
GreenRay Solar Systems 69918
 
6.7%
SunWave Energy 68786
 
6.6%
SunRise Renewable Solutions 68526
 
6.5%
PowerSun Technologies 65982
 
6.3%
EcoPower Solar 65825
 
6.3%
SunBeam Energy Solutions 62247
 
5.9%
InfiniteLight Solar 62212
 
5.9%
SolarEdge Systems 57364
 
5.5%
RadiantSun Energy 57177
 
5.5%
Other values (10) 400400
38.2%

Length

2025-03-25T23:24:19.844978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
solar 330450
 
14.2%
energy 233926
 
10.1%
systems 161280
 
6.9%
solutions 159111
 
6.8%
technologies 117865
 
5.1%
power 85975
 
3.7%
enterprises 80334
 
3.5%
skypower 70095
 
3.0%
greenray 69918
 
3.0%
sunwave 68786
 
3.0%
Other values (19) 948353
40.8%

Most occurring characters

ValueCountFrequency (%)
e 2108823
 
10.5%
n 1674418
 
8.4%
o 1633537
 
8.2%
r 1562755
 
7.8%
S 1467420
 
7.3%
1277561
 
6.4%
a 1149638
 
5.7%
l 1043273
 
5.2%
s 943184
 
4.7%
t 834638
 
4.2%
Other values (26) 6343573
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20038820
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2108823
 
10.5%
n 1674418
 
8.4%
o 1633537
 
8.2%
r 1562755
 
7.8%
S 1467420
 
7.3%
1277561
 
6.4%
a 1149638
 
5.7%
l 1043273
 
5.2%
s 943184
 
4.7%
t 834638
 
4.2%
Other values (26) 6343573
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20038820
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2108823
 
10.5%
n 1674418
 
8.4%
o 1633537
 
8.2%
r 1562755
 
7.8%
S 1467420
 
7.3%
1277561
 
6.4%
a 1149638
 
5.7%
l 1043273
 
5.2%
s 943184
 
4.7%
t 834638
 
4.2%
Other values (26) 6343573
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20038820
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2108823
 
10.5%
n 1674418
 
8.4%
o 1633537
 
8.2%
r 1562755
 
7.8%
S 1467420
 
7.3%
1277561
 
6.4%
a 1149638
 
5.7%
l 1043273
 
5.2%
s 943184
 
4.7%
t 834638
 
4.2%
Other values (26) 6343573
31.7%
Distinct360
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-25T23:24:20.064893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5454702
Min length7

Characters and Unicode

Total characters8960199
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-11-26
2nd rowDeclined
3rd row2024-12-08
4th rowDeclined
5th row2024-10-11
ValueCountFrequency (%)
declined 736858
70.3%
pending 17135
 
1.6%
2024-08-03 1574
 
0.2%
2024-07-30 1570
 
0.1%
2024-08-06 1538
 
0.1%
2024-08-05 1533
 
0.1%
2024-08-10 1533
 
0.1%
2024-08-01 1520
 
0.1%
2024-07-31 1515
 
0.1%
2024-08-12 1495
 
0.1%
Other values (350) 282261
 
26.9%
2025-03-25T23:24:20.378812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1490851
16.6%
n 771128
8.6%
2 763073
8.5%
d 753993
8.4%
i 753993
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 636362
7.1%
- 589078
 
6.6%
Other values (10) 991147
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8960199
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1490851
16.6%
n 771128
8.6%
2 763073
8.5%
d 753993
8.4%
i 753993
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 636362
7.1%
- 589078
 
6.6%
Other values (10) 991147
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8960199
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1490851
16.6%
n 771128
8.6%
2 763073
8.5%
d 753993
8.4%
i 753993
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 636362
7.1%
- 589078
 
6.6%
Other values (10) 991147
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8960199
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1490851
16.6%
n 771128
8.6%
2 763073
8.5%
d 753993
8.4%
i 753993
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 636362
7.1%
- 589078
 
6.6%
Other values (10) 991147
11.1%
Distinct357
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.5 MiB
2025-03-25T23:24:20.599458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.5339055
Min length7

Characters and Unicode

Total characters8948073
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-11-28
2nd rowDeclined
3rd row2024-12-12
4th rowDeclined
5th row2024-10-18
ValueCountFrequency (%)
declined 736858
70.3%
pending 21177
 
2.0%
2024-08-05 1551
 
0.1%
2024-08-15 1548
 
0.1%
2024-08-06 1539
 
0.1%
2024-08-14 1518
 
0.1%
2024-08-12 1516
 
0.1%
2024-08-09 1513
 
0.1%
2024-08-02 1508
 
0.1%
2024-08-08 1502
 
0.1%
Other values (347) 278302
 
26.5%
2025-03-25T23:24:20.900056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1494893
16.7%
n 779212
8.7%
i 758035
8.5%
d 758035
8.5%
2 753135
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 627598
7.0%
- 580994
 
6.5%
Other values (10) 985597
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8948073
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1494893
16.7%
n 779212
8.7%
i 758035
8.5%
d 758035
8.5%
2 753135
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 627598
7.0%
- 580994
 
6.5%
Other values (10) 985597
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8948073
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1494893
16.7%
n 779212
8.7%
i 758035
8.5%
d 758035
8.5%
2 753135
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 627598
7.0%
- 580994
 
6.5%
Other values (10) 985597
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8948073
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1494893
16.7%
n 779212
8.7%
i 758035
8.5%
d 758035
8.5%
2 753135
8.4%
l 736858
8.2%
D 736858
8.2%
c 736858
8.2%
0 627598
7.0%
- 580994
 
6.5%
Other values (10) 985597
11.0%
Distinct344
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T23:24:21.143100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.4041984
Min length7

Characters and Unicode

Total characters8812071
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-09
2nd rowDeclined
3rd row2024-12-30
4th rowDeclined
5th row2024-11-20
ValueCountFrequency (%)
declined 736858
70.3%
pending 66511
 
6.3%
2024-09-04 1443
 
0.1%
2024-09-02 1434
 
0.1%
2024-09-05 1426
 
0.1%
2024-09-01 1417
 
0.1%
2024-09-06 1415
 
0.1%
2024-09-10 1408
 
0.1%
2024-08-29 1396
 
0.1%
2024-09-03 1387
 
0.1%
Other values (334) 233837
 
22.3%
2025-03-25T23:24:21.501535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1540227
17.5%
n 869880
9.9%
i 803369
9.1%
d 803369
9.1%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 618244
7.0%
0 541473
 
6.1%
- 490326
 
5.6%
Other values (10) 934609
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8812071
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1540227
17.5%
n 869880
9.9%
i 803369
9.1%
d 803369
9.1%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 618244
7.0%
0 541473
 
6.1%
- 490326
 
5.6%
Other values (10) 934609
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8812071
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1540227
17.5%
n 869880
9.9%
i 803369
9.1%
d 803369
9.1%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 618244
7.0%
0 541473
 
6.1%
- 490326
 
5.6%
Other values (10) 934609
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8812071
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1540227
17.5%
n 869880
9.9%
i 803369
9.1%
d 803369
9.1%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 618244
7.0%
0 541473
 
6.1%
- 490326
 
5.6%
Other values (10) 934609
10.6%
Distinct336
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T23:24:21.734120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3899728
Min length7

Characters and Unicode

Total characters8797155
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-12-17
2nd rowDeclined
3rd rowPending
4th rowDeclined
5th row2024-12-03
ValueCountFrequency (%)
declined 736858
70.3%
pending 71483
 
6.8%
2024-09-11 1431
 
0.1%
2024-09-18 1401
 
0.1%
2024-09-19 1387
 
0.1%
2024-09-10 1384
 
0.1%
2024-09-09 1376
 
0.1%
2024-09-13 1375
 
0.1%
2024-09-17 1374
 
0.1%
2024-09-15 1374
 
0.1%
Other values (326) 229089
 
21.8%
2025-03-25T23:24:22.078048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1545199
17.6%
n 879824
10.0%
i 808341
9.2%
d 808341
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 607097
 
6.9%
0 525984
 
6.0%
- 480382
 
5.5%
Other values (10) 931413
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8797155
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1545199
17.6%
n 879824
10.0%
i 808341
9.2%
d 808341
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 607097
 
6.9%
0 525984
 
6.0%
- 480382
 
5.5%
Other values (10) 931413
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8797155
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1545199
17.6%
n 879824
10.0%
i 808341
9.2%
d 808341
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 607097
 
6.9%
0 525984
 
6.0%
- 480382
 
5.5%
Other values (10) 931413
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8797155
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1545199
17.6%
n 879824
10.0%
i 808341
9.2%
d 808341
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 607097
 
6.9%
0 525984
 
6.0%
- 480382
 
5.5%
Other values (10) 931413
10.6%
Distinct331
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.4 MiB
2025-03-25T23:24:22.578342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.3786141
Min length7

Characters and Unicode

Total characters8785245
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2024-12-20
2nd rowDeclined
3rd rowPending
4th rowDeclined
5th row2024-12-13
ValueCountFrequency (%)
declined 736858
70.3%
pending 75453
 
7.2%
2024-09-22 1429
 
0.1%
2024-09-16 1395
 
0.1%
2024-09-23 1389
 
0.1%
2024-09-21 1388
 
0.1%
2024-09-19 1370
 
0.1%
2024-09-18 1364
 
0.1%
2024-09-27 1357
 
0.1%
2024-09-29 1356
 
0.1%
Other values (321) 225173
 
21.5%
2025-03-25T23:24:22.937087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1549169
17.6%
n 887764
10.1%
i 812311
9.2%
d 812311
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 598295
 
6.8%
0 514273
 
5.9%
- 472442
 
5.4%
Other values (10) 928106
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8785245
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1549169
17.6%
n 887764
10.1%
i 812311
9.2%
d 812311
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 598295
 
6.8%
0 514273
 
5.9%
- 472442
 
5.4%
Other values (10) 928106
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8785245
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1549169
17.6%
n 887764
10.1%
i 812311
9.2%
d 812311
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 598295
 
6.8%
0 514273
 
5.9%
- 472442
 
5.4%
Other values (10) 928106
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8785245
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1549169
17.6%
n 887764
10.1%
i 812311
9.2%
d 812311
9.2%
l 736858
8.4%
c 736858
8.4%
D 736858
8.4%
2 598295
 
6.8%
0 514273
 
5.9%
- 472442
 
5.4%
Other values (10) 928106
10.6%
Distinct317
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.3 MiB
2025-03-25T23:24:23.307538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2593588
Min length7

Characters and Unicode

Total characters8660202
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowPending
2nd rowDeclined
3rd rowPending
4th rowDeclined
5th row2024-12-27
ValueCountFrequency (%)
declined 736858
70.3%
pending 117134
 
11.2%
2024-10-25 1201
 
0.1%
2024-10-26 1199
 
0.1%
2024-10-23 1191
 
0.1%
2024-10-20 1188
 
0.1%
2024-10-21 1179
 
0.1%
2024-11-01 1175
 
0.1%
2024-10-17 1175
 
0.1%
2024-10-09 1170
 
0.1%
Other values (307) 185062
 
17.6%
2025-03-25T23:24:23.669186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1590850
18.4%
n 971126
11.2%
i 853992
9.9%
d 853992
9.9%
l 736858
8.5%
c 736858
8.5%
D 736858
8.5%
2 493770
 
5.7%
0 411829
 
4.8%
- 389080
 
4.5%
Other values (10) 884989
10.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8660202
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1590850
18.4%
n 971126
11.2%
i 853992
9.9%
d 853992
9.9%
l 736858
8.5%
c 736858
8.5%
D 736858
8.5%
2 493770
 
5.7%
0 411829
 
4.8%
- 389080
 
4.5%
Other values (10) 884989
10.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8660202
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1590850
18.4%
n 971126
11.2%
i 853992
9.9%
d 853992
9.9%
l 736858
8.5%
c 736858
8.5%
D 736858
8.5%
2 493770
 
5.7%
0 411829
 
4.8%
- 389080
 
4.5%
Other values (10) 884989
10.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8660202
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1590850
18.4%
n 971126
11.2%
i 853992
9.9%
d 853992
9.9%
l 736858
8.5%
c 736858
8.5%
D 736858
8.5%
2 493770
 
5.7%
0 411829
 
4.8%
- 389080
 
4.5%
Other values (10) 884989
10.2%

Interactions

2025-03-25T23:24:12.826969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-25T23:24:23.734658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Acceptance StatusApplication NumberGenderProduction Capacity (KW)State/UTVendor Organization
Acceptance Status1.0000.0020.0000.0020.1150.000
Application Number0.0021.0000.0030.0010.0000.000
Gender0.0000.0031.0000.0010.0020.000
Production Capacity (KW)0.0020.0010.0011.0000.0020.000
State/UT0.1150.0000.0020.0021.0000.001
Vendor Organization0.0000.0000.0000.0000.0011.000

Missing values

2025-03-25T23:24:13.465373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-25T23:24:14.692355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
0FemaleKeralaPalakkadKerala State Electricity Board (KSEB)2024-11-03Accepted3 - 4 KW930086872024-11-15SkyPower Solar2024-11-262024-11-282024-12-092024-12-172024-12-20Pending
1FemaleTripuraSepahijalaTripura State Electricity Corporation Limited (TSECL)2024-08-23Rejected3 - 4 KW49656872DeclinedGreenEnergy SystemsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
2MaleGujaratDangTorrent Power Limited, Ahmedabad2024-11-21Accepted4 - 5 KW403959802024-12-01EcoPower Solar2024-12-082024-12-122024-12-30PendingPendingPending
3MaleRajasthanBikanerJodhpur Vidyut Vitran Nigam Limited (JdVVNL)2024-07-31Rejected2 - 3 KW89040771DeclinedGreenRay Solar SystemsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
4FemaleHaryanaRohtakDakshin Haryana Bijli Vitran Nigam (DHBVN)2024-09-23Accepted3 - 4 KW557852442024-09-30BrightSun Power2024-10-112024-10-182024-11-202024-12-032024-12-132024-12-27
5FemaleRajasthanJhunjhunuJodhpur Vidyut Vitran Nigam Limited (JdVVNL)2024-03-13Accepted3 - 4 KW589103972024-03-27PowerSun Technologies2024-04-062024-04-082024-05-032024-05-162024-05-262024-06-10
6MaleRajasthanBundiAjmer Vidyut Vitran Nigam Ltd2024-12-19Rejected3 - 4 KW31825645DeclinedSkyPower SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
7FemaleMadhya PradeshJabalpurEssel Vidyut Vitran Ujjain Pvt. Ltd.2024-06-11Accepted3 - 4 KW591828712024-06-26InfiniteLight Solar2024-07-022024-07-042024-08-122024-08-262024-08-302024-09-10
8MaleGujaratKachchhUttar Gujarat Vij Company Limited (UGVCL), Mehsana2024-11-02Rejected4 - 5 KW61138788DeclinedRadiantSun EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
9FemaleGujaratTapiMadhya Gujarat Vij Company Limited (MGVCL), Vadodara2024-12-08Accepted3 - 4 KW843720132024-12-13IlluminateSun Technologies2024-12-202024-12-25PendingPendingPendingPending
GenderState/UTDistrictDiscom NameRegistration DateAcceptance StatusProduction Capacity (KW)Application NumberApplication Approved DateVendor OrganizationVendor Selection DateVendor Acceptance DateInstallation DateInspection DateSubsidy Redeemed DateSubsidy Released Date
1048522MaleUttar PradeshJhansiMadhyanchal Vidyut Vitaran Nigam Limited (MVVNL), Lucknow Zone2024-10-23Rejected3 - 4 KW75602994DeclinedGreenRay Solar SystemsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048523FemaleOdishaMalkangiriNorth Eastern Electricity Supply Company of Odisha Ltd (NESCO)2024-06-26Rejected4 - 5 KW88203475DeclinedEcoPower SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048524MaleGoaNorth GoaGoa Electricity Department2024-09-05Rejected3 - 4 KW76823904DeclinedSolarPeak InnovationsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048525FemaleMadhya PradeshNeemuchMadhya Pradesh Poorv Kshetra Vidyut Vitaran Company Limited2024-04-11Rejected3 - 4 KW63408993DeclinedSunWave EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048526FemaleChhattisgarhKondagaonPowerGrid Corporation of India2024-09-07Rejected3 - 4 KW68005509DeclinedSunRise Renewable SolutionsDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048527MaleUttar PradeshMathuraPashchimanchal Vidyut Vitran Nigam Limited (PVVNL), Meerut Zone2024-02-16Rejected3 - 4 KW28548849DeclinedInfiniteLight SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048528FemaleGujaratSuratTorrent Power Limited, Ahmedabad2024-11-29Rejected3 - 4 KW54697160DeclinedInfiniteLight SolarDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048529MaleTelanganaJogulamba GadwalNorthern Power Distribution Company of Telangana Limited (TSNPDCL)2024-03-26Rejected4 - 5 KW85811050DeclinedRadiantSun EnergyDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048530MalePunjabPatialaPunjab State Power Corporation Limited (PSPCL)2024-10-18Rejected3 - 4 KW90024187DeclinedPowerSun TechnologiesDeclinedDeclinedDeclinedDeclinedDeclinedDeclined
1048531FemaleGujaratPatanTorrent Power Limited, Ahmedabad2024-09-20Accepted3 - 4 KW688718532024-09-27InfiniteLight Solar2024-10-062024-10-092024-10-282024-11-062024-11-102024-12-16